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Data Engineering Lead

Version 1 · Mumbai, MH, India
// classified as
Other (Adjacent or hard to classify.)
posted
1d ago
location
Mumbai, MH, India
languages
java, python, sql
tools
aws, databricks, dbt
> stack
javapythonsqlawsdatabricksdbtoraclesnowflakesparkairflowdbt
> description

Job Description

  • 8+ years’ experience in hands‑on data engineering, including technical leadership on production platforms 

  • We were looking for stronger hands-on technical depth across areas such as building production-grade data pipelines, data quality and validation, Databricks governance/access management, real-time processing, and data security. 

  • We were looking for practical experience in designing solutions, explaining technical decisions and trade-offs, and solving complex data engineering problems. 

  • Candidates who have influenced design and technical decisions with trade offs and rationale. 

  • Clear, hands-on involvement and ownership across the full lifecycle from design, implementation, testing, Security, Governance, deployment, production support. 

  • Enterprise-scale environments, large data volumes (between 10s to 100s TBs ),  

  • Comfortable working with multiple stakeholders (BAs, Architect, Data Scientist, end user). 

  • Experience providing technical governance (design reviews, standards, delivery assurance) and supporting delivery at pace  

  • Comfortable contributing to estimation and commercial discussions and ensuring solutions are feasible and deliverable  

  • Proven ability to mentor and help develop engineers through coaching, feedback, and structured development support  

  • Strong hands‑on coding skills in Python, Java, or similar languages, with strong SQL capability  

  • Proven experience building and operating batch and streaming pipelines in production  

  • Experience with AWS, Databricks / Spark, and modern data architectures  

  • Hands‑on experience using dbt for transformations and Airflow (or equivalent) for orchestration  

  •  Solid understanding of data modelling, data quality, and production data systems  

  • Experience working with relational databases such as Postgres or SQL Server  

  • Familiarity with CI/CD pipelines, testing frameworks, and monitoring / observability tooling 

Qualifications

  • Experience enabling ML, AI, or GenAI workloads through strong data foundations 

  • Exposure to modern BI and analytics tooling 

  • Experience working in regulated or security‑conscious environments 

  • Consulting or client‑facing delivery experience 

Additional Information

Why Version 1? 

 At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing, professional growth, and financial stability. 

  • Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits 
  • Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme 
  • Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance 
  • Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme 
  • Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies 
  • Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat 
  • Reward schemes including Version 1’s Annual Excellence Awards & ‘Call-Out’ platform. 
  • Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes. 

And many more exciting benefits… drop us a note to find out more.    

Version 1 is an equal opportunities employer. 
 
We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring. 
 
We want every candidate to have a positive and accessible recruitment experience. If you need reasonable adjustments at any stage of the process, please contact [recruiter email address] at Version 1. We will consider all requests carefully, respectfully and confidentially. 

Version 1 is an equal opportunities employer. 

We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring including those shaped by disability and neurodiversity. 

We want every candidate to have a positive and accessible recruitment experience. If you need reasonable adjustments at any stage of the process, please contact your recruiter at Version 1. We will consider all requests carefully, respectfully and confidentially. 

Video links: https://www.youtube.com/watch?v=F_d3ELTH5zo 

Company Description

Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. 

The Role

We are looking for a Data Tech Lead to join our Data Engineering practice, delivering modern data platforms for enterprise and regulated clients. This is a hands‑on leadership role for a technically strong engineer who can lead design and delivery, act as a trusted technical authority, and mentor engineers while maintaining strong engineering discipline in real‑world environments. 

This is a delivery‑focused role for an experienced engineer and Tech Lead who enjoys solving complex data challenges, takes ownership of outcomes, and applies strong engineering discipline in real‑world environments. 

What You’ll Be Doing 

  • Leading end‑to‑end delivery of data engineering workstreams; shaping solution approach, setting technical direction, and ensuring outcomes are delivered to a high standard 

  • Designing and building scalable batch and streaming pipelines and operating production systems 

  • Providing technical governance and oversight: design reviews, implementation guidance, risk/issue escalation, and delivery assurance 

  • Building strong stakeholder relationships and operating as a credible client‑facing technical lead 

  • Coaching and mentoring engineers, supporting learning plans, and helping develop capability standards and accelerators 

  • Partnering with business and technology stakeholders to build and enhance reliable, scalable data platforms  

  • Developing high‑throughput, low‑latency data processing systems  

  • Working within the Databricks and Apache Spark ecosystem to support large‑scale data workloads  

  • Building and maintaining cloud‑native data solutions on AWS  

  • Using dbt for data transformation, modelling, testing, and documentation  

  • Orchestrating data workflows using Airflow or similar orchestration tools  

  • Writing clean, efficient, and well‑tested code following software engineering best practices  

  • Collaborating closely with product, analytics, and platform teams  

  • Supporting production systems by troubleshooting issues and implementing continuous improvements 

  • Ensuring solutions are production‑ready: secure, tested, observable, and cost‑efficient 

  • Optimising data performance, reliability, and data quality in live environments 

Apply at Version 1 →